Higher order statistical approach to nonlinear stochastic optimal control problem

Jemin George, Puneet Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents the formulation of an optimal control methodology for nonlinear stochastic systems, where the control objective is to obtain a feedback law that would minimize the higher order statistics associated with the traditional integral quadratic cost. The two part control scheme proposed here consist of approximating the probability density function associated with the nonlinear plant by the Gaussian sum approach and utilizing the existing deterministic optimal control schemes to obtain a feedback law that would minimize the higher order statistics that is of interest. Since both components are interdependent, an iterative scheme is required to obtain the optimal solution.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference and Exhibit
StatePublished - Dec 1 2009
EventAIAA Guidance, Navigation, and Control Conference and Exhibit - Chicago, IL, United States
Duration: Aug 10 2009Aug 13 2009

Publication series

NameAIAA Guidance, Navigation, and Control Conference and Exhibit

Other

OtherAIAA Guidance, Navigation, and Control Conference and Exhibit
CountryUnited States
CityChicago, IL
Period8/10/098/13/09

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Higher order statistical approach to nonlinear stochastic optimal control problem'. Together they form a unique fingerprint.

  • Cite this

    George, J., & Singla, P. (2009). Higher order statistical approach to nonlinear stochastic optimal control problem. In AIAA Guidance, Navigation, and Control Conference and Exhibit [2009-5880] (AIAA Guidance, Navigation, and Control Conference and Exhibit).